Ontology-based Complementary Breastfeeding Search Model

Astrid Noviana Paradhita, A. Sari, Agus Sihabuddin
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引用次数: 0

Abstract

Children's nutritional requirements differ from those of adults. The health ministry's Indonesian data shows that in 2017, there were 17.8% of malnourished children under five years old (toddlers), one of which was related to complementary breastfeeding problems. Complementary breastfeeding is given to babies starting at 6–24 months of age. This research aims to build a complementary breastfeeding search model and be able to present it as a treatment for malnourished babies. A search model is built to understand natural language input given by a user. Also, it can do reasoning by applying a set of rules to obtain implicit knowledge about the complementary breastfeeding menu recommended for babies. The methods used in this research are data collection, designing a search model, building an ontology model, building SWRL, natural language processing, and usability testing by users and nutritionists. This research succeeded in building an ontology-based complementary breastfeeding search model in the form of a semantic web. The testing result shows that the web can provide an alternative complementary breastfeeding menu according to the baby’s nutritional needs and has a high usability capability of 4.01 on a scale of 1 to 5.
基于本体的补充母乳喂养搜索模型
儿童的营养需求与成人不同。印尼卫生部的数据显示,2017年,五岁以下儿童(学步儿童)营养不良的比例为17.8%,其中之一与补充母乳喂养问题有关。从6至24个月大的婴儿开始接受补充母乳喂养。这项研究旨在建立一个补充母乳喂养的搜索模型,并能够将其作为营养不良婴儿的治疗方法。建立了一个搜索模型来理解用户给出的自然语言输入。此外,它还可以通过应用一套规则进行推理,以获得关于推荐给婴儿的补充母乳喂养菜单的隐性知识。本研究使用的方法包括数据收集、设计搜索模型、构建本体模型、构建SWRL、自然语言处理以及用户和营养师的可用性测试。本研究成功地以语义网的形式构建了一个基于本体的补充母乳喂养搜索模型。测试结果表明,该网站可以根据婴儿的营养需求提供替代性的补充母乳喂养菜单,在1-5分的范围内具有4.01的高可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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20
审稿时长
12 weeks
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